ETAP PS vs. Posit

ETAP is highly recommended for evaluating static conditions in electrical power systems, whether in high or medium complexity networks. For example, study of load flow, analysis of frequency harmonics.

On the other hand, I would not recommend ETAP for the simulation of highly complex control systems that require a dynamic analysis of the variables.

In my humble opinion, if you are working on something related to Statistics, RStudio is your go-to tool. But if you are looking for something in Machine Learning, look out for Python. The beauty is that there are packages now by which you can write Python/SQL in R. Cross-platform functionality like such makes RStudio way ahead of its competition. A couple of chinks in RStudio armor are very small and can be considered as nagging just for the sake of argument. Other than completely based on programming language, I couldn't find significant drawbacks to using RStudio. It is one of the best free software available in the market at present.

Incentivized

• Excellent facility for the design of electrical systems, since it has multiple options and configuration.
• Truly intuitive, it is easy to adapt to the user interface, so the learning curve is very fast.
• It offers a wide variety of electrical studies that can be carried out, therefore it is very versatile for multiple applications.

• The support is incredibly professional and helpful, and they often go out of their way to help me when something doesn't work.
• The one-click publishing from RStudio Connect is absolutely amazing, and I really like the way that it deploys your exact package versions, because otherwise, you can get in a terrible mess.
• Python doesn't feel quite as native as R at the moment but I have definitely deployed stuff in R and Python that works beautifully which is really nice indeed.

Incentivized

• Perhaps the interface is somewhat confusing the first time you use the program.
• It offers a wide configuration, which can be overwhelming.
• Sometimes the program can freeze depending on the size of the electrical grid that is being simulated. This also depends on the software requirements.

• Python integration is newer and still can be rough, especially with when using virtual environments.
• RStudio Connect pricing feels very department focused, not quite an enterprise perspective.
• Some of the RStudio packages don't follow conventional development guidelines (API breaking changes with minor version numbers) which can make supporting larger projects over longer timeframes difficult.

Incentivized

There is no viable alternative right now. The toolset is good and the functionality is increasing with every release. It is backed by regular releases and ongoing development by the RStudio team. There is good engagement with RStudio directly when support is required. Also there's a strong and growing community of developers who provide additional support and sample code.

Incentivized

ETAP PS is really easy to use. When recreating the power system to be simulated, it is easy to obtain a result close to reality due to the multiple components offered in the interface. As for the electrical studies available, they are simple to execute and require really little configuration to make them work, always offering a wide variety of options to adjust the program to the simulation of the desired condition.

For someone who learns how to use the software and picks up on the "language" of R, it's very easy to use. For beginners, it can be hard and might require a course, as well as the appropriate statistical training to understand what packages to use and when

Incentivized

RStudio is very available and cheap to use. It needs to be updated every once in a while, but the updates tend to be quick and they do not hinder my ability to make progress. I have not experienced any RStudio outages, and I have used the application quite a bit for a variety of statistical analyses

Incentivized

Sometimes when the program crashes for a random reason, it is difficult to find a direct solution to the problem. I think better documentation is needed for this type of case. Still, more and more people are sharing their work on the web, making it easier to orient yourself when these issues occur.

Since R is trendy among statisticians, you can find lots of help from the data science/ stats communities. If you need help with anything related to RStudio or R, google it or search on StackOverflow, you might easily find the solution that you are looking for.

Incentivized

We did it at the individual level: anyone willing to code in R can use it. No real deployment involved.

Simulink allows to analyze and simulate different variables with respect to time in an electric power system, but it is more focused on visual programming On the other hand, ETAP is better designed for static simulation of power systems, offering options and studies in a very more direct and easier to execute.

RStudio was provided as the most customizable. It was also strictly the most feature-rich as far as enabling our organization to script, run, and make use of R open-source packages in our data analysis workstreams. It also provided some support for python, which was useful when we had R heavy code with some python threaded in. Overall we picked Rstudio for the features it provided for our data analysis needs and the ability to interface with our existing resources.

Incentivized

RStudio is very scalable as a product. The issue I have is that it doesn't necessarily fit in nicely with the mainly Microsoft environment that everybody else is using. Having RStudio for us means dedicated servers and recruiting staff who know how to manage the environment. This isn't a fault of the product at all, it's just part of the data science landscape that we all have to put up with. Having said that RStudio is absolutely great for running on low spec servers and there are loads of options to handle concurrency, memory use, etc.

Incentivized

• Improves the reliability of the electrical system.
• Study of the system operations, allowing a better adjustment of the facilities that are in production.
• Provides results that allow you to select solutions for energy saving.

• Using it for data science in a very big and old company, the most positive impact, from my point of view, has been the ability of spreading data culture across the group. Shortening the path from data to value.
• Still it's hard to quantify economic benefits, we are struggling and it's a great point of attention, since splitting out the contribution of the single aspects of a project (and getting the RStudio pie) is complicated.
• What is sure is that, in the long run, RStudio is boosting productivity and making the process in which is embedded more efficient (cost reduction).

Incentivized